JOURNAL ARTICLE

Accurate mobile robot position determination using unscented Kalman filter

Abstract

The objective is to accurately determine mobile robots position and orientation by integrating information received from odometry and an inertial sensor. The position and orientation provided by odometry are subject to different types of errors. To improve the odometry, a fiber optic gyroscope is used to give the orientation information that is more reliable. The information from odometry and gyroscope are integrated using unscented Kalman filter (UKF). The position and orientation determined using the UKF is compared with the results from the extended Kalman filter (EKF)

Keywords:
Odometry Extended Kalman filter Kalman filter Gyroscope Computer vision Orientation (vector space) Artificial intelligence Computer science Mobile robot Visual odometry Position (finance) Inertial measurement unit Fast Kalman filter Robot Engineering Mathematics Aerospace engineering

Metrics

17
Cited By
1.18
FWCI (Field Weighted Citation Impact)
13
Refs
0.89
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Inertial Sensor and Navigation
Physical Sciences →  Engineering →  Aerospace Engineering
Target Tracking and Data Fusion in Sensor Networks
Physical Sciences →  Computer Science →  Artificial Intelligence
Robotics and Sensor-Based Localization
Physical Sciences →  Engineering →  Aerospace Engineering

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